class_docstr: Implement a base class     for the :term:`General Linear Model<GLM>`.
docstr: Transform voxelwise r-squared values to the same shape         as the input Nifti1Image(s).
  
  Returns
  -------
  output : list
      A list of Nifti1Image(s).
docstr_tok: ["Transform","voxelwise","r-squared","values","to","the","same","shape","as","the","input","Nifti1Image","(","s",")",".","Returns","--","--","--","-","output",":","list","A","list","of","Nifti1Image","(","s",")","."]
code: def r_square(self):
      """Transform voxelwise r-squared values to the same shape \
          as the input Nifti1Image(s).
  
          Returns
          -------
          output : list
              A list of Nifti1Image(s).
  
          """
      return self._get_voxelwise_model_attribute(
          "r_square", result_as_time_series=False
      )
  
file_path: nilearn/nilearn/glm/_base.py
imports: from nibabel.onetime import auto_attr
  from sklearn.base import BaseEstimator, TransformerMixin
  from nilearn._utils import CacheMixin
label_desc: Use image node_id 3 for calling the BaseGLM obj's underlying member method code with example usage: obj.r_square() and returns: self